Evaluation value calculation device and electronic endoscope system

ABSTRACT

An electronic endoscope system includes a plotting unit which plots pixel correspondence points, which correspond to pixels that constitute an intracavitary color image that has a plurality of color components, on a target plane according to color components of the pixel correspondence points, the target plane intersecting the origin of a predetermined color space; an axis setting unit which sets a reference axis in the target plane based on pixel correspondence points plotted on the target plane; and an evaluation value calculating unit which calculates a prescribed evaluation value with respect to the captured image based on a positional relationship between the reference axis and the pixel correspondence points.

TECHNICAL FIELD

The present invention relates to an evaluation value calculation deviceand an electronic endoscope system for calculating a prescribedevaluation value.

BACKGROUND ART

A lesion site generally has a different color from normal mucosaltissue. In recent years, improvements in the performance of colorendoscope apparatuses have made it possible for an operator to identifyand diagnose a lesion site whose color is slightly different from normaltissue. However, an operator needs extensive training under the guidanceof an expert in order to be able to accurately distinguish a lesion sitefrom normal tissue based on a slight color difference in an imagecaptured by an endoscope and then make a diagnosis. Also, even anexperienced operator may not be able to easily identify and diagnose alesion site based on a slight color difference, and this requirescareful work.

In view of this, JP 2014-18332A (referred to hereinafter as “PatentDocument 1”) is one example of a document that describes a device forscoring a lesion site that appears in a captured image in order tofacilitate the diagnosis of a lesion site by an operator. Specifically,with the device described in Patent Document 1, the pixels thatconstitute an image captured by an endoscope are subjected to toneenhancement processing for applying non-linear gain to the pixel values,the dynamic range is widened in the vicinity of the boundary of a regionof pixel values that are to be subjected to lesion site determination,the tone-enhanced pixel data in an RGB space, which is defined by thethree primary colors RGB, is converted to a predetermined color spacesuch as the HIS color space or the HSV color space in order to acquirehue and saturation information, pixels are determined to be or not belesion site pixels based on the acquired hue and saturation information,and then an evaluation value (lesion index) is calculated based on thenumber of pixels determined to be lesion site pixels.

SUMMARY OF INVENTION

In evaluation value calculation devices that calculate an evaluationvalue, typified by the device illustrated in Patent Document 1, even inthe case of imaging the same subject, the evaluation value obtained as aresult of calculation may change due to differences between electronicendoscope models, change over time, and the like. As a countermeasure,it is conceivable to perform calibration in order to suppress variationin the evaluation value caused by differences between electronicendoscope models, change over time, and the like.

However, in order to perform calibration, it is generally necessary tomanufacture a jig dedicated for calibration, and perform atime-consuming operation such as performing calibration imaging usingthe dedicated jig in advance.

The present invention was achieved in light of the above-describedsituation, and an object thereof is to provide an evaluation valuecalculation device and an electronic endoscope system that do not need adedicated jig or a time-consuming operation when performing calibration.

An electronic endoscope system according to an embodiment of the presentinvention includes: a plotting means for plotting pixel correspondencepoints, which correspond to pixels that constitute an intracavitarycolor image that has a plurality of color components, on a target planeaccording to color components of the pixel correspondence points, thetarget plane intersecting an origin of a predetermined color space; anaxis setting means for setting a reference axis in the target planebased on pixel correspondence points plotted on the target plane; and anevaluation value calculating means for calculating a prescribedevaluation value with respect to the captured image based on apositional relationship between the reference axis and the pixelcorrespondence points.

Also, in an embodiment of the present invention, the target plane is aplane that includes an R component axis, for example.

Also, in an embodiment of the present invention, the target plane is aplane that further includes a G component axis, for example.

Also, in an embodiment of the present invention, the reference axis isan axis drawn on a boundary line between a region in which the pixelcorrespondence points are distributed and a region in which pixelcorrespondence points are not distributed in the target plane, forexample.

Also, in an embodiment of the present invention, a configuration ispossible in which the plotting means plots the pixel correspondencepoints in a predetermined section of the target plane. The section isdefined by first and second axes that pass through the origin, forexample. Letting the origin be a start point of the first and secondaxes, and other ends of the first and second axes be end points of theaxes, the axis setting means may detect a pixel correspondence pointthat is located on a line segment connecting the end point of the secondaxis and the end point of the first axis and that is closest to the endpoint of the second axis, and set an axis that connects the detectedpixel correspondence point and the start point as the reference axis.

Also, in an embodiment of the present invention, a configuration ispossible in which the axis setting means partitions the target planeinto a first region and a second region using the reference axis. Inthis case, the evaluation value calculating means calculates theprescribed evaluation value using pixel correspondence points plotted inthe first region. Also, the axis setting means sets the reference axisin a manner according to which the number of pixel correspondence pointsplotted in the second region falls in a predetermined range.

Also, in an embodiment of the present invention, a configuration ispossible in which the axis setting means sets the reference axis eachtime the color image is captured by an image capturing means, or only ata predetermined timing.

Also, in an embodiment of the present invention, a configuration ispossible in which the axis setting means calculates a provisionalreference axis each time a predetermined timing is reached, and sets thereference axis based on the provisional reference axes calculated at thetimings.

Also, in an embodiment of the present invention, the reference axis isan axis having a high correlation with a hue of a mucous membrane in abody cavity, for example.

Also, in an embodiment of the present invention, the prescribedevaluation value is a numerical representation of an abnormal portion ina body cavity, for example.

Also, an evaluation value calculation device according to an embodimentof the present invention includes: a plotting means for plotting pixelcorrespondence points, which correspond to pixels that constitute anintracavitary color image that has a plurality of color components, on atarget plane according to color components of the pixel correspondencepoints, the target plane intersecting an origin of a predetermined colorspace; an axis setting means for setting a reference axis in the targetplane based on pixel correspondence points plotted on the target plane;and an evaluation value calculating means for calculating a prescribedevaluation value with respect to the captured image based on apositional relationship between the reference axis and the pixelcorrespondence points.

Also, an evaluation value calculation device according to an embodimentof the present invention includes: an image capturing means forcapturing a color image that has R (Red), G (Green), and B (Blue) colorcomponents; a plotting means for plotting pixel correspondence points,which correspond to pixels that constitute a captured image obtained bythe image capturing means, on a plane according to color components ofthe pixel correspondence points, the plane including a first axis thatis an R component axis and a second axis that is a G component axis andis orthogonal to the first axis; an axis setting means for setting areference axis that passes through an intersection of the first axis andthe second axis in the plane and is not parallel with each of the firstaxis and the second axis, based on pixel correspondence points plottedon the plane; and an evaluation value calculating means for calculatinga prescribed evaluation value with respect to the captured image basedon a positional relationship between the reference axis and the pixelcorrespondence points.

Also, in an embodiment of the present invention, a start point of thefirst axis and a start point of the second axis are at the samelocation, for example. In this case, a configuration is possible inwhich the axis setting means detects a pixel correspondence point thatis located on a line segment connecting an end point of the second axisand an end point of the first axis and that is closest to the end pointof the second axis, and sets an axis that connects the detected pixelcorrespondence point and the start point as the reference axis.

Also, in an embodiment of the present invention, a configuration ispossible in which the axis setting means sets the reference axis eachtime the captured image is captured by the image capturing means, oronly at a predetermined timing.

Also, in an embodiment of the present invention, a configuration ispossible in which the axis setting means calculates a provisionalreference axis each time a predetermined timing is reached, and sets thereference axis based on the provisional reference axes calculated at thetimings.

Also, in an embodiment of the present invention, the reference axis isan axis having a high correlation with a hue of a mucous membrane in abody cavity, for example.

Also, in an embodiment of the present invention, the prescribedevaluation value is a numerical representation of an abnormal portion ina body cavity, for example.

Also, an evaluation value calculation device according to an embodimentof the present invention may be for incorporation into an electronicendoscope system.

Also, in an embodiment of the present invention, the reference axis isan axis drawn on a boundary line between a region in which the pixelcorrespondence points are distributed and a region in which pixelcorrespondence points are not distributed in the target plane.

According to an embodiment of the present invention, an evaluation valuecalculation device and an electronic endoscope system that do not need adedicated jig or a time-consuming operation when performing calibrationare provided.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram showing a configuration of an electronicendoscope system according to an embodiment of the present invention.

FIG. 2 is a diagram showing a flowchart of special image generationprocessing performed by a special image processing circuit included in aprocessor according to an embodiment of the present invention.

FIG. 3 is a diagram for assisting a description of a reference axis AXsetting method in processing step S12 in FIG. 2.

FIG. 4 is a diagram for assisting a description of degree ofinflammation calculation processing in processing step S14 in FIG. 2.

FIG. 5 is a diagram for assisting a description of degree ofinflammation calculation processing in processing step S14 in FIG. 2.

FIG. 6 is a diagram showing an example of a display screen displayed ona monitor display screen in a special mode according to an embodiment ofthe present invention.

FIG. 7 is a diagram showing a flowchart of mucous membrane variationaxis (reference axis AX) setting processing, which is executed in avariation of the embodiment of the present invention.

FIG. 8 is a diagram for assisting a description of setting processingaccording to the variation in FIG. 7.

FIG. 9 is a diagram showing a flowchart of inflammation evaluation valuecalculation processing according to another embodiment of the presentinvention.

DESCRIPTION OF EMBODIMENTS

Hereinafter, embodiments of the present invention will be described withreference to the drawings. Note that an electronic endoscope system istaken as an example of an embodiment of the present invention in thefollowing description.

Configuration of Electronic Endoscope System 1

FIG. 1 is a block diagram showing the configuration of an electronicendoscope system 1 according to an embodiment of the present invention.As shown in FIG. 1, the electronic endoscope system 1 includes anelectronic endoscope 100, a processor 200, and a monitor 300.

The processor 200 includes a system controller 202 and a timingcontroller 204. The system controller 202 executes various programsstored in a memory 222 and performs overall control of the electronicendoscope system 1. Also, the system controller 202 is connected to anoperation panel 218. The system controller 202 changes operations of theelectronic endoscope system 1 and parameters for various operation inaccordance with instructions from an operator that are input using theoperation panel 218. One example of an instruction input by an operatoris an instruction for switching the operating mode of the electronicendoscope system 1. In the present embodiment, the operating modesinclude a normal mode and a special mode. The timing controller 204outputs a clock pulse, which is for adjustment of the timing of theoperations of portions, to circuits in the electronic endoscope system1.

A lamp 208 is activated by a lamp power supply igniter 206, andthereafter emits white light L. The lamp 208 is a high-intensity lampsuch as a xenon lamp, a halogen lamp, a mercury lamp, or a metal halidelamp. The white light L emitted by the lamp 208 is condensed by acondensing lens 210 and limited to an appropriate light amount via adiaphragm 212. Note that the lamp 208 may be replaced with asemiconductor light emitting element such as an LD (Laser Diode) or anLED (Light Emitting Diode). Note that a semiconductor light emittingelement has features such as having a lower power consumption andsmaller heat emission amount than other light sources, and therefore hasan advantage of making it possible to acquire bright images while alsosuppressing power consumption and the heat emission amount. The abilityto acquire bright images leads to an improvement in the precision of alater-described inflammation evaluation value.

A motor 214 is mechanically coupled to the diaphragm 212 viatransmission mechanisms such as an arm and a gear, which are not shown.The motor 214 is a DC motor for example, and is driven under drivecontrol of a driver 216. The diaphragm 212 is operated by the motor 214,and the opening degree is changed in order to set the images displayedon the display screen of a monitor 300 to an appropriate brightness. Thelight amount of the white light L emitted by the lamp 208 is limitedaccording to the opening degree of the diaphragm 212. The appropriateimage brightness reference is set and changed according to an intensityadjustment operation performed on the operation panel 218 by theoperator. Note that the light control circuit for performing intensityadjustment by controlling the driver 216 is a known circuit and will notbe described in this specification.

The white light L that passes through the diaphragm 212 is condensed onthe entrance end face of an LCB (Light Carrying Bundle) 102 and entersthe LCB 102. The white light L that entered the LCB 102 through theentrance end face propagates inside the LCB 102. After propagatinginside the LCB 102, the white light L exits through an exit end face ofthe LCB 102 arranged at the leading end of the electronic endoscope 100,passes through a light distribution lens 104, and illuminates biologicaltissue. Returning light from the biological tissue illuminated by thewhite light L passes through an objective lens 106 and forms an opticalimage on the light receiving surface of a solid-state imaging element108.

The solid-state imaging element 108 is a single-plate color CCD (ChargeCoupled Device) image sensor that has a Bayer pixel arrangement. Thesolid-state imaging element 108 accumulates charge according to thelight quantity of an optical image formed on pixels on the lightreceiving surface, generates R (Red), G (Green), and B (Blue) imagesignals, and outputs the image signals. Hereinafter, the image signalsof respective pixels (pixel addresses) that are sequentially output bythe solid-state imaging element 108 will be referred to as “pixelsignals”. Note that the solid-state imaging element 108 is not limitedto being a CCD image sensor, and may be replaced with a CMOS(Complementary Metal Oxide Semiconductor) image sensor or another typeof imaging apparatus. The solid-state imaging element 108 may be anelement that includes a complementary color filter. One example of acomplementary color filter is a CMYG (Cyan, Magenta, Yellow, Green)filter.

A primary color (RGB) filter has better color characteristics than acomplementary color filter. For this reason, the evaluation precisioncan be improved by performing inflammation evaluation value calculationusing RGB image signals obtained by an imaging element that includes aprimary color filter. Also, using a primary color filter eliminates theneed to perform signal conversion in later-described inflammationevaluation value calculation processing. For this reason, it is possibleto suppress the processing burden of inflammation evaluation valuecalculation.

A driver signal processing circuit 112 is provided in the connectionportion of the electronic endoscope 100. Pixel signals from biologicaltissue illuminated by white light L are input by the solid-state imagingelement 108 to the driver signal processing circuit 112 at a framecycle. The pixel signals input from the solid-state imaging element 108are output by the driver signal processing circuit 112 to a pre-stagesignal processing circuit 220 of the processor 200. Note that the terms“frame” and “field” may be switched in the following description. In thepresent embodiment, the frame cycle and the field cycle are respectively1/30 seconds and 1/60 seconds.

The driver signal processing circuit 112 also accesses a memory 114 andreads out unique information regarding the electronic endoscope 100. Theunique information regarding the electronic endoscope 100 recorded inthe memory 114 includes, for example, the pixel count, sensitivity,operable frame rate, and model number of the solid-state imaging element108. The unique information read out from the memory 114 is output bythe driver signal processing circuit 112 to a system controller 202.

The system controller 202 generates control signals by performingvarious computation based on the unique information regarding theelectronic endoscope 100. The system controller 202 uses the generatedcontrol signals to control the operations of and the timing of variouscircuits in the processor 200 so as to perform processing suited to theelectronic endoscope that is connected to the processor 200.

A timing controller 204 supplies a clock pulse to the driver signalprocessing circuit 112 in accordance with timing control performed bythe system controller 202. In accordance with the clock pulse suppliedfrom the timing controller 204, the driver signal processing circuit 112controls the driving of the solid-state imaging element 108 according toa timing synchronized with the frame rate of the images processed by theprocessor 200.

Operations in Normal Mode

The following describes signal processing operations in the processor200 in the normal mode.

The pre-stage signal processing circuit 220 performs demosaic processingon R, G, and B pixel signals received from the driver signal processingcircuit 112 at the frame cycle. Specifically, R pixel signals aresubjected to interpolation processing using G and B surrounding pixels,G pixel signal are subjected to interpolation processing using R and Bsurrounding pixels, and B pixel signals are subjected to interpolationprocessing using R and G surrounding pixels. Accordingly, the pixelsignals that only had information regarding one color component areconverted into pixel data that has information regarding the three R, G,and B color components. Note that in the present embodiment, the pixeldata obtained after demosaicing has 8-bit (0-255) information for eachof the R, G, and B color components.

The pre-stage signal processing circuit 220 performs predeterminedsignal processing such as a matrix operation, white balance adjustmentprocessing, and gamma correction processing on the pixel data obtainedafter demosaic processing, and outputs the resulting data to a specialimage processing circuit 230.

The special image processing circuit 230 performs pass-through output ofthe pixel data received from the pre-stage signal processing circuit 220to the post-stage signal processing circuit 240.

The post-stage signal processing circuit 240 performs predeterminedsignal processing on the pixel data received from the special imageprocessing circuit 230 to generate screen data for monitor display, andconverts the generated monitor display screen data into a predeterminedvideo format signal. The converted video format signal is output to themonitor 300. Accordingly, color images of the biological tissue aredisplayed on the display screen of the monitor 300.

Operations in Special Mode

Next, signal processing operations in the processor 200 in the specialmode will be described.

The pre-stage signal processing circuit 220 performs predeterminedsignal processing such as demosaic processing, a matrix operation, whitebalance adjustment processing, and gamma correction processing on pixelsignals received from the driver signal processing circuit 112 at theframe cycle, and outputs the resulting data to the special imageprocessing circuit 230.

Special Image Generation Processing

FIG. 2 shows a flowchart of special image generation processingperformed by the special image processing circuit 230. The special imagegeneration processing in FIG. 2 is started at the time when theoperating mode of the electronic endoscope system 1 is set to thespecial mode, and a freeze button of the electronic endoscope 100 hasbeen pressed (when a still image capture operation has been performed),for example.

S11 in FIG. 2 (Input of Pixel Data of Current Frame)

In this processing step S11, pixel data for each pixel of the currentframe (when the capture operation is performed) is received from thepre-stage signal processing circuit 220.

S12 in FIG. 2 (Setting of Reference Axis AX)

In this processing step S12, the reference axis AX that is to be usedwhen calculating the degree of inflammation of the target illness isset. FIG. 3 is a diagram for assisting the description of a referenceaxis AX setting method, and shows an RG plane defined by an R axis and aG axis that are orthogonal to each other (more specifically, shows asection in the RG plane defined by the two R and G axes). The R axis isthe axis for the R component (R pixel values), and the G axis is theaxis for the G component (G pixel values).

In this processing step S12, pixel data (three-dimensional data) foreach pixel in the RGB space defined by the three primary colors RGB isconverted into RG two-dimensional data and plotted in the RG planeaccording to the R and G pixel values as shown in FIG. 3. Hereinafter,for the sake of convenience in the description, the points correspondingto pixel data plotted on the RG plane will be referred to as “pixelcorrespondence points”. Note that the operation of plotting the pixeldata on the RG plane, which is executed in this processing step S12, isperformed by a plotting means. Also, the operation of setting thereference axis AX on the RG plane is performed by an axis setting means.

In this way, in this processing step S12, pixel of interest data(three-dimensional data) in the RGB space is orthographically projectedonto the RG plane, and the pixel of interest correspondence points(two-dimensional data) are the feet of vertical lines dropped onto theRG plane from the points in the RGB plane that correspond to the pixelof interest data.

Due to influences such as hemoglobin coloring, the R component isdominant over the other components (G component and B component) in thebody cavity of the patient that is to be imaged, and the redness (i.e.,R component) typically increases the more intense the inflammation is.For this reason, the R axis value of the pixel correspondence point isbasically thought to be proportional to the degree of inflammation.However, in images captured inside a body cavity, the hue variesaccording to imaging conditions that influence brightness (e.g., degreeof illumination with white light L). For example, shaded portions notreached by the white light L are black (achromatic), and portions wherethe white light L strikes intensely and is specularly reflected arewhite (achromatic). In other words, depending on the degree ofillumination with the white light L, the R axis value of the pixelcorrespondence point may take a value that has no correlation with thedegree of inflammation. Accordingly, it is difficult to preciselyevaluate the degree of inflammation with only the R component.

Generally, normal sites inside a body cavity that are not inflamed aresufficiently covered by a mucous membrane. In contrast, abnormal sitesinside a body cavity that are inflamed are not sufficiently covered by amucous membrane. The mucous membrane is thinner the greater the degreeof inflammation is at an abnormal site such as a lesion site. A mucousmembrane is basically white in color, but has a slightly yellowish hue,and the hue (yellow hue) that appears in an image varies according tothe darkness/lightness (membrane thickness). Accordingly, thedarkness/lightness of the mucous membrane is also thought to be anindicator for evaluating the degree of inflammation.

In view of this, in this processing step S12, a reference axis AX is setas shown in FIG. 3 so as to pass through the intersection (origin) ofthe R axis and the G axis in the RG plane and also not be parallel witheach of the R axis and the G axis. Specifically, the pixelcorrespondence point that is located on a line segment connecting theend point of the G axis and the end point of the R axis, both of whichhave the same start point (both start points being the origin (0,0)),and that is the closest to the end point of the G axis (in the examplein FIG. 3, the pixel correspondence point indicated with the referencesign α) is detected. Next, the axis that connects the detected pixelcorrespondence point α and the start points of the R axis and the G axis(i.e., the origin (0,0)) is set as the reference axis AX.

The reference axis AX is the variation axis of the hue in which thecolor component that is a mixture of the R component and the G component(i.e., the yellow component) is dominant, and has a high correlationwith mucous membrane darkness/lightness (mucous membrane hue). As aresult of the inventor of the present invention analyzing many sampleimages taken inside body cavities, it was found that, as shown in theexample in FIG. 3, in the RG plane, when an axis is drawn between thestart points of the R axis and the G axis and the pixel correspondencepoint α that is located on a line segment connecting the end point ofthe G axis and the end point of the R axis and is located the closest tothe end point of the G axis, two regions separated by the drawn axis(reference axis AX) appear, namely a region in which pixelcorrespondence points are distributed and a region in which pixelcorrespondence points are not distributed. The reference axis AX thathas a high correlation with change in the mucous membrane hue will bereferred to hereinafter as the “mucous membrane variation axis” for thesake of convenience in the description.

For better understanding, it is thought that the pixel correspondencepoints in the RG plane are distributed in the region sandwiched betweenthe axes indicating blood and a mucous membrane. For this reason, theboundary line between the region in which pixel correspondence pointsare distributed and the region in which pixel correspondence points arenot distributed corresponds to the axis that indicates the mucousmembrane (mucous membrane variation axis). Given that the pointindicated by the reference sign α is a point located on the boundaryline, the reference axis AX that connects the point α and the origin isdefined as the mucous membrane variation axis.

Additionally, the region in which pixel correspondence points aredistributed is the region in the RG plane that indicates hues that canappear when imaging a target illness. Also, the region in which pixelcorrespondence points are not distributed is the region in which the RGplane that indicates hues that cannot appear when imaging a targetillness.

In this way, in the present embodiment, in the process of executing thespecial image generation processing shown in FIG. 2, calibration(setting of the reference axis AX that can change due to differencesbetween models, change over time, and the like in the electronicendoscope 100) is automatically executed using an actual intracavitarycaptured image. Accordingly, there is no need for a troublesomeoperation and a dedicated tool that are conventionally necessary forcalibration.

S13 in FIG. 2 (Selection of Pixel of Interest)

In this processing step S13, one pixel of interest is selected fromamong all of the pixels in accordance with a predetermined sequence.Hereinafter, for the sake of convenience in the description, the pointscorresponding to pixel of interest data plotted on the RG plane (and onthe later-described R-mucous membrane plane) will be referred to as“pixel of interest correspondence points”.

S14 in FIG. 2 (Calculation of Degree of Inflammation)

In this processing step S14, the degree of inflammation is calculatedfor the pixel of interest that was selected in processing step S13(selection of pixel of interest). FIGS. 4 and 5 are diagrams forassisting the description of degree of inflammation calculationprocessing.

In this processing step S14, as shown in FIG. 4, the plane in which theR axis and the mucous membrane variation axis are orthogonal (referredto hereinafter as the “R-mucous membrane plane” for the sake ofconvenience in the description) is defined, and the pixel of interestdata (pixel of interest correspondence points) plotted on the RG planeare subjected to projective transformation (orthographic projectivetransformation) onto the R-mucous membrane plane. Note that as a resultof the inventor of the present invention analyzing many sample images ofmucous membranes inside body cavities, it was found that the R axisvalues of the pixel correspondence points that were subjected toprojective transformation onto the R-mucous membrane plane are under 128at their highest. In view of this, in the R-mucous membrane plane, the Raxis is compressed to 7 bits in order to reduce the calculationprocessing burden. Also, the mucous membrane variation axis is expressedin 8 bits.

Next, two coefficients (hemoglobin coefficient and mucous membranecoefficient) that increase in value as the degree of inflammation risesare applied to the pixel of interest correspondence points, and theapplied hemoglobin coefficient and mucous membrane coefficient aremultiplied.

The hemoglobin coefficient is a coefficient that rises in proportion tothe R axis value, and is correlated with the degree of inflammation. Inthe present embodiment, the hemoglobin coefficient matches the R axisvalue. For example, if the R axis value of the pixel of interestcorrespondence point is 10, “10” is applied as the hemoglobincoefficient to the pixel of interest correspondence point, and if the Raxis value of the pixel of interest correspondence point is 250, “250”is applied as the hemoglobin coefficient to the pixel of interestcorrespondence point.

The mucous membrane coefficient is a coefficient that decreases as themucous membrane variation axis value rises, and in the presentembodiment, it is a value obtained by subtracting the mucous membranevariation axis value from the value of 255. From another viewpoint, themucous membrane coefficient is a coefficient that increases as themucous membrane variation axis value decreases, and rises the thinnerthe mucous membrane is (the greater the degree of inflammation is). Forexample, if the mucous membrane variation axis value of the pixel ofinterest correspondence point is 10, “245(=255−10)” is applied as themucous membrane coefficient to the pixel of interest correspondencepoint, and if the R axis value of the pixel of interest correspondencepoint is 250, “5(=255−250)” is applied as the mucous membranecoefficient to the pixel of interest correspondence point.

The multiplied value of the hemoglobin coefficient and the mucousmembrane coefficient is divided by 128, which is the maximum value ofthe hemoglobin coefficient. Accordingly, a degree of inflammation thatfalls within the range of 0 to 255 is calculated for the pixel ofinterest.

In this way, in this processing step S14, only division that can beperformed by bit shift calculation is performed when calculating thedegree of inflammation. For this reason, floating-point calculation isnot necessary, and the processing burden in degree of inflammationcalculation is low.

FIG. 5 is a diagram illustrating the relationship between the degree ofinflammation calculated in this processing step S14 and brightness in aintracavitary captured image.

In FIG. 5, the degree of inflammation increases the farther the pixelcorresponding to the pixel correspondence point is located in thedirection indicated by an arrow A. In other words, in FIG. 5, the degreeof inflammation decreases the farther away the pixel corresponding tothe pixel correspondence point is located in the upper left region wherethe hemoglobin coefficient and the mucous membrane coefficient are bothlow, and increases the farther away the pixel corresponding to the pixelcorrespondence point is located in the lower right region where thehemoglobin coefficient and the mucous membrane coefficient are bothhigh.

On the other hand, if brightness in the intracavitary captured imagechanges according to the degree of illumination with white light L, thehue in the captured image is influenced by individual differences, theimaging location, the state of inflammation, and the like, but isbasically thought to change in the same manner for each of the colorcomponents. According to this thinking, the intracavitary captured imageincreases in brightness the farther away the pixel corresponding to thepixel correspondence point is located in the direction indicated by anarrow B in FIG. 5. In other words, in FIG. 5, the intracavitary capturedimage decreases in brightness the farther away the pixel correspondingto the pixel correspondence point is located in the lower left regionwhere the R axis and mucous membrane variation axis values are both low,and increases in brightness the farther away the pixel corresponding tothe pixel correspondence point is located in the upper right regionwhere the R axis and mucous membrane variation axis values are both low.

As shown in FIG. 5, in the R-mucous membrane plane, the direction ofhigh correlation with change in the degree of inflammation (arrow Adirection) is approximately orthogonal to the direction of highcorrelation with change in brightness in a captured image (arrow Bdirection). Based on this, it is understood that the degree ofinflammation calculated in this processing step S14 is a value that issubstantially not influenced by change in brightness in the capturedimage.

S15 in FIG. 2 (Determination of Display Color in Color Map Image)

In the present embodiment, it is possible to display a color map imageobtained by mosaicking a captured image in display colors thatcorrespond to the degree of inflammation. In order to enable the displayof a color map image, a table of correspondence between degree ofinflammation values and predetermined display colors is stored in astorage region such as the memory 222. In this table, a display color isassociated with each group of 5 values, for example. For example, yellowis associated with the range of degree of inflammation values 0 to 5,different display colors are associated with groups of five highervalues according to the color order in the hue circle, and red isassociated with the range of values 250 to 255.

In this processing step S15, the display color in the color map imagefor the pixel of interest selected in processing step S13 (selection ofpixel of interest) is determined to be, based on the above-describedtable, the color that corresponds to the value of the degree ofinflammation of the pixel of interest that was calculated in processingstep S14 (calculation of degree of inflammation).

S16 in FIG. 2 (Determination of Completion of Execution of Processingfor all Pixels)

In this processing step S16, it is determined whether or not processingsteps S13 to S15 have been executed for all of the pixels in the currentframe.

If a pixel not yet subjected to processing steps S13 to S15 remains(S16: NO), the procedure in the special image generation processing inFIG. 2 returns to processing step S13 (selection of pixel of interest)in order to execute processing steps S13 to S15 on the next pixel ofinterest.

S17 in FIG. 2 (Calculation of Inflammation Evaluation Value)

Step S17 of this processing is executed if it is determined inprocessing step S16 (determination of completion of execution ofprocessing for all pixels) that processing steps S13 to S15 have beenexecuted on all of the pixels in the current frame (S16: YES). In thisprocessing step S17, an average value obtained by averaging the degreeof inflammation of all of the pixels in the current frame is calculatedas the overall inflammation evaluation value of the captured image, anddisplay data for the calculated inflammation evaluation value (exampleof display data: Score: OO) is generated. Note that the operation ofcalculating an inflammation evaluation value as a prescribed evaluationvalue for a color image, which is executed in this processing step S17,is performed by an evaluation value calculating means.

S18 in FIG. 2 (Overlay Processing)

In this processing step S18, a coefficient is set as the ratio foroverlaying a normal image, which is based on pixel data received fromthe pre-stage signal processing circuit 220 (i.e., pixel data having thethree R, G, and B color components), and a color map image, which isbased on pixel data including predetermined display colors that weredetermined in processing step S15 (determination of display color incolor map image), and the former pixel data (normal pixel data) and thelatter pixel data (color map pixel data) are added based on thecoefficient. The setting of the coefficient can be appropriately changedby a user operation. In the case of a desire to display the normal imagemore, the coefficient for the normal pixel data is set higher, and inthe case of a desire to display the color map image more, thecoefficient for the color map pixel data is set higher.

S19 in FIG. 2 (End Determination)

In this processing step S19, it is determined whether or not theoperating mode of the electronic endoscope system 1 has been switched toa mode other than the special mode. If it is determined that theoperating mode has not been switched to another mode (S19: NO), theprocedure in the special image generation processing in FIG. 2 returnsto processing step S11 (input of pixel data of current frame). However,if it is determined that the operating mode has been switched to anothermode (S19: YES), the special image generation processing in FIG. 2 ends.

Screen Display Example

The post-stage signal processing circuit 240 generates display data foran overlay image including the normal image and the color map imagebased on the pixel data obtained by the addition processing inprocessing step S18 (overlay processing) in FIG. 2, performs maskingprocessing for masking the peripheral region of the display screen ofthe monitor 300 (periphery of the image display region), and furthermoregenerates monitor display screen data in which the inflammationevaluation value is superimposed on the mask region generated by themasking processing. The post-stage signal processing circuit 240converts the generated monitor display screen data into a predeterminedvideo format signal, and outputs the signal to the monitor 300.

FIG. 6 shows an example of screen display in the special mode. As shownin FIG. 6, the display screen of the monitor 300 includes theintracavitary captured image (overlay image in which the normal imageand the color map image are overlaid) in the central region, and amasked screen region surrounding the image display region. Theinflammation evaluation value (score) is also displayed in the maskregion.

In this way, according to the present embodiment, there is no need toperform complex color space transformation processing, nonlinearcalculation processing such as tone enhancement processing, or the like,and an inflammation evaluation value (here, a value correlated withincrease/decrease in the hemoglobin coloring of an imaging site) isobtained by merely performing simple calculation processing. In otherwords, the amount of hardware resources needed for calculation of aninflammation evaluation value is significantly suppressed. Also, theinflammation evaluation value substantially does not vary according toimaging conditions that influence the brightness of the intracavitarycaptured image (e.g., the degree of illumination with irradiationlight), and therefore the operator can make a more objective andaccurate diagnosis regarding inflammation.

Also, in the present embodiment, calibration is automatically executedin the processor 200 in the process of calculating a degree ofinflammation, thus eliminating the need for a dedicated jig or atime-consuming operation that have conventionally been required forcalibration.

Also, the electronic endoscope system according to the presentembodiment achieves effects and problem solutions such as the followingin the applicable technical fields.

First, the electronic endoscope system according to the presentembodiment is a diagnostic aid for early discovery of an inflammatoryillness.

Second, according to the configuration of the present embodiment, it ispossible to display a screen showing the degree of inflammation orenhance the image in a region in which inflammation is occurring, suchthat the operator can discover mild inflammation that is difficult toview. In particular, mild inflammation is difficult to distinguish froma normal site, and therefore the effects achieved by the configurationof the present embodiment regarding the evaluation of mild inflammationare remarkable.

Third, according to the configuration of the present embodiment, it ispossible to provide the operator with an objective evaluation value asan evaluation of the degree of inflammation, thus making it possible toreduce differences in diagnoses among operators. In particular, there isa large advantage of being able to provide an operator having littleexperience with an objective evaluation value obtained by theconfiguration of the present embodiment.

Fourth, according to the configuration of the present embodiment, theburden of image processing is reduced, thus making it possible toperform real-time display of images of an inflamed site. This makes itpossible to improve diagnosis precision.

Fifth, according to the configuration of the present embodiment, theprocessing burden of evaluation value calculation is reduced incomparison with the background technology described above, thus makingit possible to display a color map image (image showing the degree ofinflammation) and a normal image side-by-side or in a composited mannerwithout lag. For this reason, it is possible to display a color mapimage without extending the inspection time, thus making it possible toavoid an increase in the burden on the patient.

The site that is to be observed in the present embodiment is arespiratory organ or the like, or a digestive organ or the like, forexample. Here, “respiratory organ or the like” includes the lungs, theears, the nose, and the throat, for example. “Digestive organ or thelike” includes the large intestine, the small intestine, the stomach,the duodenum, and the uterus, for example. The electronic endoscopesystem according to the present embodiment is thought to have even moreremarkable effects when the observation target is the large intestine.The following are specific reasons for this.

The large intestine is susceptible to diseases that can be evaluatedusing inflammation as a reference, and the advantage of discoveringinflamed sites is greater than in the case of other organs. Inparticular, the inflammation evaluation value obtained by the presentembodiment is effective as an indicator of inflammatory bowel disease(IBD), which is typified by ulcerative colitis. A method of treatmenthas not been established for ulcerative colitis, and therefore using theelectronic endoscope system having the configuration of the presentembodiment is very effective in making an early diagnosis andsuppressing the progression of the illness.

The large intestine is a narrower and longer organ than the stomach andthe like, and the obtained images have greater depth and are darker asthe depth increases. According to the configuration of the presentembodiment, it is possible to suppress variation in the evaluation valuecaused by changes in the brightness in the image. Accordingly, when theelectronic endoscope system according to the present embodiment isapplied to the observation of the large intestine, the effects of thepresent embodiment are remarkable. In other words, the electronicendoscope system according to the present embodiment is preferably arespiratory organ electronic endoscope system or a digestive organelectronic endoscope system, and is more preferably a large intestineelectronic endoscope system.

Also, although mild inflammation is generally difficult to diagnose,according to the configuration of the present embodiment, by displayingthe results of degree of inflammation evaluation on the screen forexample, it is possible to avoid a situation in which the operatormisses mild inflammation. In particular, in the case of mildinflammation, the determination criteria are not clear, and this is afactor that causes a large amount of individual differences betweenoperators. In this regard as well, according to the configuration of thepresent embodiment, it is possible to provide the operator with anobjective evaluation value, thus making it possible to reduce variationin diagnoses caused by individual differences.

Note that the above-described configuration of the present embodiment isapplicable to the calculation of an evaluation value of not only thedegree of inflammation, but also cancer, polyps, and various otherlesions that are accompanied by a color change, and advantageous effectssimilar to those described above can be achieved in these other cases aswell. In other words, the evaluation value of the present embodiment ispreferably an evaluation value for a lesion that is accompanied by acolor change, and includes an evaluation value of at least any ofinflammation, cancer, and polyps.

An illustrative embodiment of the present invention has been describedabove. The embodiments of the present invention are not limited to theembodiment described above, and various changes can be made withoutdeparting from the scope of the technical idea of the present invention.For example, appropriate combinations of embodiments and the likeexplicitly given as examples in this specification and obviousembodiments and the like are also encompassed in embodiments of thepresent invention.

In the above embodiment, calibration (setting of the reference axis AX)is executed only at the timing when the freeze button of the electronicendoscope 100 is pressed (i.e., when a still image is captured), but thepresent invention is not limited to this. Calibration may be executedone time during moving image shooting (e.g., when a predetermined timehas elapsed since power on) or constantly (each time a frame image iscaptured).

In the above embodiment, calibration (setting of the reference axis AX)is executed based on information included in a captured imagecorresponding to one frame, but the present invention is not limited tothis. For example, biological tissue in a body cavity is covered by amucous membrane and has glossiness. For this reason, when irradiationlight is specularly reflected and then incident on the light receivingsurface of the imaging element, there are cases where blown-outhighlights appear at biological tissue located in a specular reflectionregion, and a proper observation image is not obtained. In view of this,in another embodiment, a provisional reference axis AX is calculatedeach time a frame image is captured when the freeze button of theelectronic endoscope 100 is pressed, for example. Next, when aprovisional reference axis AX has been calculated for captured imagescorresponding to n (n being a natural number of 2 or more) frames, thereference axis AX (definitive value) is set based on the n provisionalreference axes AX that were calculated. The reference axis AX(definitive value) is, for example, the median value or the averagevalue of the n provisional reference axes AX.

In the above embodiment, the inflammation evaluation value is calculatedusing the R component and the G component (RG two-dimensional colorspace) included in the pixels, but in another embodiment, by usinganother two-dimension color space such as RB in place of the RGtwo-dimensional color space, or a three-dimensional color space such asHSI, HSV, or Lab, it is possible to calculate an evaluation value thatcorresponds to the other color space and is related to a target illnessdifferent from that of the above embodiment.

Although an evaluation value for inflammation or the like is calculatedusing R, G, and B primary color components in the above embodiment, theconfiguration for calculating an evaluation value of the presentinvention is not limited to using the R, G, and B primary colorcomponents. A configuration is possible in which in place of using theR, G, and B primary color components, the C, M, Y, and G (Cyan, Magenta,Yellow, and Green) complementary color components are used to calculatean evaluation value for inflammation or the like with a method similarto that of the above embodiment.

Although the light source portion that includes the lamp power supplyigniter 206, the lamp 208, the condensing lens 210, the diaphragm 212,the motor 214, and the like is provided integrated with the processor inthe above embodiment, the light source portion may be provided as adevice that is separate from the processor.

As described in the above embodiment, a CMOS image sensor may be used inplace of a CCD image sensor as the solid-state imaging element 108. Ingeneral, with a CMOS image sensor, the image tends to be overall darkerthan in the case of a CCD image sensor. Accordingly, with theconfiguration of the above embodiment, the advantageous effect of beingable to suppress variation in the evaluation value caused by imagebrightness is even more remarkable in a situation where a CMOS imagesensor is used as the solid-state imaging element.

In order to precisely make a diagnosis, it is preferable to obtainhigh-definition images. Accordingly, from the viewpoint of furtherimproving diagnosis precision, the image resolution is preferably 1million pixels or more, more preferably 2 million pixels or more, andfurther preferably 8 million pixels or more. The higher the resolutionof the image is, the greater the burden becomes in processing forcalculating the above-described evaluation value for all of the pixels.However, according to the configuration of the above embodiment, it ispossible to suppress the processing burden in evaluation valuecalculation, and therefore the advantageous effect of the configurationof the present embodiment is remarkable in the situation of processing ahigh-definition image.

Although all of the pixels in the image are subjected to processing inthe special image generation processing in the above embodiment, pixelswith a very high luminance, pixels with a very low luminance, or thelike may be excluded from the target of processing. Specifically, theprecision of the evaluation value can be improved by performingevaluation value calculation on only pixels determined to have aluminance in a predetermined reference luminance range, for example.

As described in the above embodiment, various types of light sources canbe used as the light source used in the electronic endoscope system 1.However, a mode is also possible in which the type of light source islimited depending on the observation target of the electronic endoscopesystem 1 or the like (e.g., a laser type is excluded as the type oflight source).

Also, regarding the color components used for evaluation valuecalculation, a mode is possible in which the calculation of theevaluation value using hue and saturation is excluded.

In the above embodiment, in processing step S12 (setting of referenceaxis AX) in FIG. 2, the axis connecting the pixel correspondence point αand the origin (0,0) is set as the reference axis AX (mucous membranevariation axis), but the reference axis AX setting method is not limitedto this.

FIG. 7 shows a flowchart of reference axis AX setting processing that isexecuted in a variation of the above embodiment. Also, FIG. 8(a) to FIG.8(c) are diagrams for assisting the description of the settingprocessing according to the present variation. The special imagegeneration processing according to the present variation issubstantially the same as the special image generation processingaccording to the above embodiment, with the exception that the referenceaxis AX is set by executing the setting processing shown in FIG. 7.

S51 in FIG. 7 (Plotting of Pixel Correspondence Points)

In this processing step S51, pixel correspondence points of the currentframe are plotted on the RG plane.

S52 in FIG. 7 (Initial Setting of Reference Axis AX)

In this processing step S52, as shown in FIG. 8(a), the reference axisAX is initially set on the RG plane. Initial setting data regarding thereference axis AX is stored in advance in a predetermined storage mediumsuch as a memory 222. Note that in the following, the angle formed bythe reference axis AX and the R axis is denoted by θ.

S53 in FIG. 7 (Selection of Pixel of Interest)

In this processing step S53, one pixel of interest (pixel of interestcorrespondence point) is selected from among all of the pixels inaccordance with a predetermined sequence.

S54 in FIG. 7 (Position Determination)

In the present variation, in S14 (calculation of degree of inflammation)in FIG. 2, the pixel of interest correspondence points located in theregion between the reference axis AX and the R axis (first region) areused in degree of inflammation calculation, and the pixel of interestcorrespondence points located in the region between the reference axisAX and the G axis (second region) are not used in degree of inflammationcalculation. In this processing step S54, it is determined whether ornot the pixel of interest correspondence point that was selected inprocessing step S53 (selection of pixel of interest) is located in thesecond region.

S55 in FIG. 7 (Count Processing)

This processing step S55 is executed if it is determined in processingstep S54 (position determination) that the pixel of interestcorrespondence point is located in the second region (S54: YES). In thisprocessing step S55, a count value C of a counter in the special imageprocessing circuit 230 is incremented by one. Note that the count valueC is reset to zero at the time when the execution of the settingprocessing shown in FIG. 7 is started, for example.

S56 in FIG. 7 (Determination of Completion of Execution of Processingfor all Pixels)

In this processing step S56, it is determined whether or not processingsteps S53 to S54 have been executed on all of the pixel correspondencepoints that were plotted in processing step S51 (plotting of pixelcorrespondence points).

If a pixel correspondence point not yet subjected to processing stepsS53 to S54 remains (S56: NO), the setting processing shown in FIG. 7returns to processing step S53 (selection of pixel of interest) in orderto execute processing on the next pixel of interest correspondencepoint.

S57 in FIG. 7 (Determination Regarding Count Value C)

Step S57 of this processing is executed if it is determined inprocessing step S56 (determination of completion of execution ofprocessing for all pixels) that processing steps S53 to S54 have beenexecuted on all of the pixel correspondence points (S56: YES). In thisprocessing step S57, it is determined whether or not the count value Cis greater than a predetermined upper threshold value.

S58 in FIG. 7 (Increasing of Angle θ)

Step S58 of this processing is executed if it is determined inprocessing step S57 (determination regarding count value C) that thecount value C is greater than the predetermined upper threshold value(S57: YES). In this case, there are too many pixel of interestcorrespondence points located in the second region (in other words,pixels of interest that are not to be used in degree of inflammationcalculation), and it is difficult to calculate an inflammationevaluation value with high precision. In view of this, in thisprocessing step S58, the angle θ is increased as shown in FIG. 8(b) soas to reduce the number of pixel of interest correspondence pointslocated in the second region to an appropriate number.

Note that the amount of increase in the angle θ may be a fixed value, ormay be appropriately set according to the magnitude of the count valueC. In the latter case, the amount of increase in the angle θ is setlarger the larger the count value C is, for example.

After the execution of this processing step S58, the count value C isreset to zero, and the setting processing shown in FIG. 7 returns toprocessing step S53 (selection of pixel of interest). Then, processingsteps S53 to S56 are executed with respect to the reference axis AXafter the increase in the angle θ (i.e., the number of pixel of interestcorrespondence points located in the second region after the increase inthe angle θ is counted), and then processing step S57 (determinationregarding count value C) is executed. The processing of processing stepsS53 to S58 is repeated until the count value C decreases to thepredetermined upper threshold value or lower.

S59 in FIG. 7 (Determination Regarding Count Value C)

Step S59 of this processing is executed if it is determined inprocessing step S57 (determination regarding count value C) that thecount value C is lower than or equal to the predetermined upperthreshold value (S57: NO). In this processing step S59, it is determinedwhether or not the count value C is smaller than a predetermined lowerthreshold value.

S60 in FIG. 7 (Decreasing of Angle θ)

Step S60 of this processing is executed if it is determined inprocessing step S59 (determination regarding count value C) that thecount value C is smaller than the predetermined lower threshold value(S59: YES). In this case, there are too few pixel of interestcorrespondence points located in the second region (in other words,pixels of interest that are not to be used in degree of inflammationcalculation), and there is a risk that the reference axis AX has notbeen set appropriately (e.g., the reference axis AX is located at aposition largely deviating from the region in which pixel of interestcorrespondence points are densely distributed). In view of this, in thisprocessing step S60, the angle θ is reduced as shown in FIG. 8(c) so asto increase the number of pixel of interest correspondence pointslocated in the second region to an appropriate number.

Note that the amount of decrease in the angle θ may be a fixed value, ormay be appropriately set according to the magnitude of the count valueC. In the latter case, the amount of decrease in the angle θ is setlarger the smaller the count value C is, for example.

After the execution of this processing step S60, the count value C isreset to zero, and the setting processing shown in FIG. 7 returns toprocessing step S53 (selection of pixel of interest). Then, processingsteps S53 to S56 are executed with respect to the reference axis AXafter the decrease in the angle θ (i.e., the number of pixel of interestcorrespondence points located in the second region after the decrease inthe angle θ is counted), processing step S57 (determination regardingcount value C) is executed, and then processing step S59 (determinationregarding count value C) is executed. The processing of processing stepsS53 to S60 is repeated until the count value C rises to thepredetermined lower threshold value or higher.

By repeating the increase or decrease in the angle θ, the number ofpixel of interest correspondence points located in the second regionfalls within an appropriate range (between the lower threshold value andthe upper threshold value) (S60: NO). Accordingly, highly precisecalibration (setting of the reference axis AX that can change due todifferences between models, change over time, and the like in theelectronic endoscope 100) is achieved.

In the special image generation processing shown in FIGS. 2 and 7, aninflammation evaluation value is calculated for a captured image, but inanother embodiment, an inflammation evaluation value may be calculatedfor a moving image (i.e., over multiple frames).

FIG. 9 shows a flowchart of inflammation evaluation value calculationprocessing according to another embodiment. The inflammation evaluationvalue calculation processing shown in FIG. 9 is started at the time whenthe operating mode of the electronic endoscope system 1 is switched tothe special mode, for example. Note that in the case of this otherembodiment, as is described below, only the inflammation evaluationvalue is included in the content displayed on the display screen of themonitor 300, but in this other embodiment as well, the inflammationevaluation value may be displayed on the display screen of the monitor300 along with an endoscopic image such as an overlay image, similarlyto the above embodiment.

S111 in FIG. 9 (Initial Setting of Reference Axis AX)

In this processing step S111, the reference axis AX is initially set onthe RG plane with use of initial setting data that is stored in thememory 222 or the like.

S112 in FIG. 9 (Input of Pixel Data of Current Frame)

In this processing step S112, pixel data for each pixel of the currentframe is received from the pre-stage signal processing circuit 220.

S113 in FIG. 9 (Plotting of Pixel Correspondence Points)

In this processing step S113, pixel correspondence points of the currentframe are plotted on the RG plane.

S114 in FIG. 9 (Selection of Pixel of Interest)

In this processing step S114, one pixel of interest (pixel of interestcorrespondence point) is selected from among all of the pixels inaccordance with a predetermined sequence.

S115 in FIG. 9 (Position Determination)

In this processing step S115, it is determined whether or not the pixelof interest correspondence point that was selected in processing stepS114 (selection of pixel of interest) is located in the second region.

S116 in FIG. 9 (Count Processing)

Step S116 of this processing is executed if it is determined inprocessing step S115 (position determination) that the pixel of interestcorrespondence point is located in the second region (S115: YES). Inthis processing step S116, the count value C is incremented by one. Notethat the count value C is reset to zero for each frame (e.g., each timeprocessing step S112 (input of pixel data of current frame) is executedfor the target frame), for example.

S117 in FIG. 9 (Calculation of Degree of Inflammation)

This processing step S117 is executed if it is determined in processingstep S115 (position determination) that the pixel of interestcorrespondence point is not located in the second region (in otherwords, is located in the first region) (S115: NO). In this processingstep S117, the degree of inflammation is calculated for the pixel ofinterest that was selected in processing step S114 (selection of pixelof interest).

S118 in FIG. 9 (Determination of Completion of Execution of Processingfor all Pixels)

In this processing step S118, it is determined whether or not processingsteps S114 to S115 have been executed for all of the pixels in thecurrent frame.

If a pixel not yet subjected to processing steps S114 to S115 remains(S118: NO), the procedure in the inflammation evaluation valuecalculation processing in FIG. 9 returns to processing step S114(selection of pixel of interest) in order to execute processing stepsS114 to S115 on the next pixel of interest.

S119 in FIG. 9 (Calculation of Inflammation Evaluation Value)

This processing step S119 is executed if it is determined in processingstep S118 (determination of completion of execution of processing forall pixels) that processing steps S114 to S115 have been executed on allof the pixels of the current frame (S118: YES). In this processing stepS119, an average value obtained by averaging the degrees of inflammationof the pixels calculated in processing step S117 (degree of inflammationcalculation) (in other words, only the pixels located in the firstregion) is calculated as the overall inflammation evaluation value forthe captured image, and is displayed on the display screen of themonitor 300.

S120 in FIG. 9 (Determination Regarding Count Value C)

In this processing step S120, it is determined whether or not the countvalue C is greater than a predetermined upper threshold value.

S121 in FIG. 9 (Increasing of Angle θ)

This processing step S121 is executed if it is determined in processingstep S120 (determination regarding count value C) that the count value Cis greater than the predetermined upper threshold value (S120: YES). Inthis case, there are too many pixel of interest correspondence pointslocated in the second region, and it is difficult to calculate aninflammation evaluation value with high precision. In view of this, inthis processing step S120, the angle θ is increased so as to reduce thenumber of pixel of interest correspondence points located in the secondregion to an appropriate number.

S122 in FIG. 9 (Determination Regarding Count Value C)

This processing step S122 is executed if it is determined in processingstep S120 (determination regarding count value C) that the count value Cis lower than or equal to the predetermined upper threshold value (S120:NO). In this processing step S122, it is determined whether or not thecount value C is smaller than a predetermined lower threshold value.

S123 in FIG. 9 (Decreasing of Angle θ)

This processing step S123 is executed if it is determined in processingstep S122 (determination regarding count value C) that the count value Cis smaller than the predetermined lower threshold value (S122: YES). Inthis case, there are too few pixel of interest correspondence pointslocated in the second region, and there is a risk that the referenceaxis AX has not been set appropriately. In view of this, in thisprocessing step S123, the angle θ is reduced so as to increase thenumber of pixel of interest correspondence points located in the secondregion to an appropriate number.

S124 in FIG. 9 (Determination of End of Inflammation Evaluation ValueCalculation Processing)

In this processing step S124, it is determined whether or not theoperator has switched from the special mode to another mode such as thenormal mode, for example. If the operator has not switched to anothermode (S124: NO), the inflammation evaluation value calculationprocessing in FIG. 9 returns to processing step S112 (input of pixeldata of current frame) in order to perform the calculation and displayof an inflammation evaluation value for the next frame. If the operatorhas switched to another mode (S124: YES), the inflammation evaluationvalue calculation processing in FIG. 9 ends.

According to this other embodiment, the reference axis AX issuccessively adjusted when performing moving image capturing in whichthe imaging conditions and imaging region successively change (In otherwords, the reference axis AX is re-set for each frame. Note that thereference axis AX is maintained when the number of pixel of interestcorrespondence points located in the second region falls within theappropriate range (between the lower threshold value and the upperthreshold value).). For this reason, even in a situation in which theimage conditions and imaging region successively change, theinflammation evaluation value is successively calculated with highprecision.

1-19. (canceled)
 20. An electronic endoscope system comprising: aplotting unit configured to plot pixel correspondence points, whichcorrespond to pixels that constitute an intracavitary color image thathas a plurality of color components, on a target plane according tocolor components of the pixel correspondence points, the target planeintersecting an origin of a predetermined color space; an axis settingunit configured to set a reference axis in the target plane based onpixel correspondence points plotted on the target plane; and anevaluation value calculating unit configured to calculate a prescribedevaluation value with respect to the captured image based on apositional relationship between the reference axis and the pixelcorrespondence points.
 21. The electronic endoscope system according toclaim 20, wherein the target plane is a plane that includes an Rcomponent axis.
 22. The electronic endoscope system according to claim21, wherein the target plane is a plane that further includes a Gcomponent axis.
 23. The electronic endoscope system according to claim20, wherein the reference axis is an axis drawn on a boundary linebetween a region in which the pixel correspondence points aredistributed and a region in which pixel correspondence points are notdistributed in the target plane.
 24. The electronic endoscope systemaccording to claim 20, wherein the plotting unit plots the pixelcorrespondence points in a predetermined section of the target plane,the section is defined by first and second axes that pass through theorigin, and letting the origin be a start point of the first and secondaxes, and other ends of the first and second axes be end points of theaxes, the axis setting unit detects a pixel correspondence point that islocated on a line segment connecting the end point of the second axisand the end point of the first axis and that is closest to the end pointof the second axis, and sets an axis that connects the detected pixelcorrespondence point and the start point as the reference axis.
 25. Theelectronic endoscope system according to claim 20, wherein the axissetting unit partitions the target plane into a first region and asecond region using the reference axis, the evaluation value calculatingunit calculates the prescribed evaluation value using pixelcorrespondence points plotted in the first region, and the axis settingunit sets the reference axis in a manner according to which the numberof pixel correspondence points plotted in the second region falls in apredetermined range.
 26. The electronic endoscope system according toclaim 20, wherein the axis setting unit sets the reference axis eachtime the color image is captured by an image capturing unit, or only ata predetermined timing.
 27. The electronic endoscope system according toclaim 20, wherein the axis setting unit calculates a provisionalreference axis each time a predetermined timing is reached, and sets thereference axis based on the provisional reference axes calculated at thetimings.
 28. The electronic endoscope system according to claim 20,wherein the reference axis is an axis having a high correlation with ahue of a mucous membrane in a body cavity.
 29. The electronic endoscopesystem according to claim 20, wherein the prescribed evaluation value isa numerical representation of an abnormal portion in a body cavity. 30.An evaluation value calculation device comprising: a plotting unitconfigured to plot pixel correspondence points, which correspond topixels that constitute an intracavitary color image that has a pluralityof color components, on a target plane according to color components ofthe pixel correspondence points, the target plane intersecting an originof a predetermined color space; an axis setting unit configured to set areference axis in the target plane based on pixel correspondence pointsplotted on the target plane; and an evaluation value calculating unitconfigured to calculate a prescribed evaluation value with respect tothe captured image based on a positional relationship between thereference axis and the pixel correspondence points.
 31. An evaluationvalue calculation device comprising: an image capturing unit configuredto capture a color image that has R (Red), G (Green), and B (Blue) colorcomponents; a plotting unit configured to plot pixel correspondencepoints, which correspond to pixels that constitute a captured imageobtained by the image capturing unit, on a target plane according tocolor components of the pixel correspondence points, the target planeincluding a first axis that is an R component axis and a second axisthat is a G component axis and is orthogonal to the first axis; an axissetting unit configured to set a reference axis that passes through anintersection of the first axis and the second axis in the target planeand is not parallel with each of the first axis and the second axis,based on pixel correspondence points plotted on the target plane; and anevaluation value calculating unit configured to calculate a prescribedevaluation value with respect to the captured image based on apositional relationship between the reference axis and the pixelcorrespondence points.
 32. The evaluation value calculation deviceaccording to claim 31, wherein a start point of the first axis and astart point of the second axis are at the same location, the axissetting unit detects a pixel correspondence point that is located on aline segment connecting an end point of the second axis and an end pointof the first axis and that is closest to the end point of the secondaxis, and sets an axis that connects the detected pixel correspondencepoint and the start point as the reference axis.
 33. The evaluationvalue calculation device according to claim 31, wherein the axis settingunit sets the reference axis each time the captured image is captured bythe image capturing unit, or only at a predetermined timing.
 34. Theevaluation value calculation device according to claim 31, wherein theaxis setting unit calculates a provisional reference axis each time apredetermined timing is reached, and sets the reference axis based onthe provisional reference axes calculated at the timings.
 35. Theevaluation value calculation device according to claim 31, wherein thereference axis is an axis having a high correlation with a hue of amucous membrane in a body cavity.
 36. The evaluation value calculationdevice according to claim 31, wherein the prescribed evaluation value isa numerical representation of an abnormal portion in a body cavity. 37.The evaluation value calculation device according to claim 31, whereinthe evaluation value calculation device is for incorporation in anelectronic endoscope system.
 38. The evaluation value calculation deviceaccording to claim 31, wherein the reference axis is an axis drawn on aboundary line between a region in which the pixel correspondence pointsare distributed and a region in which pixel correspondence points arenot distributed in the target plane.